Enhanced spatial analysis assessing the association between PFAS-contaminated water and cancer incidence: rationale, study design, and methods

Abstract Background Cancer is a complex set of diseases, and many have decades-long lag times between possible exposure and diagnosis. Environmental exposures, such as per- and poly-fluoroalkyl substances (PFAS) and area-level risk factors (e.g., socioeconomic variables), vary for people over time a...

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Main Authors: Resa M. Jones, Erin R. Kulick, Ryan Snead, Robin Taylor Wilson, John Hughes, Ted Lillys
Format: Article
Language:English
Published: BMC 2025-01-01
Series:BMC Cancer
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Online Access:https://doi.org/10.1186/s12885-025-13508-2
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author Resa M. Jones
Erin R. Kulick
Ryan Snead
Robin Taylor Wilson
John Hughes
Ted Lillys
author_facet Resa M. Jones
Erin R. Kulick
Ryan Snead
Robin Taylor Wilson
John Hughes
Ted Lillys
author_sort Resa M. Jones
collection DOAJ
description Abstract Background Cancer is a complex set of diseases, and many have decades-long lag times between possible exposure and diagnosis. Environmental exposures, such as per- and poly-fluoroalkyl substances (PFAS) and area-level risk factors (e.g., socioeconomic variables), vary for people over time and space. Evidence suggests PFAS exposure is associated with several cancers; however, studies to date have various limitations. Few studies have used rigorous spatiotemporal approaches, and, to our knowledge, none have assessed cumulative exposures given residential histories or incorporated chemical mixture modeling. Thus, spatiotemporal analysis using advanced statistical approaches, accounting for spatially structured and unstructured heterogeneity in risk, can be a highly informative strategy for addressing the potential health effects of PFAS exposure. Methods Using population-based incident cancer cases and cancer-free controls in a 12-county area of southeastern Pennsylvania, we will apply Bayesian spatiotemporal analysis methods using historically reconstructed PFAS-contaminated water exposure given residential histories, and other potential cancer determinants over time. Bayesian group index models enable assessment of various mixtures of highly correlated PFAS chemical exposures incorporating mobility/residential history, and contextual factors to determine the association of PFAS-related exposures and cancer incidence. Discussion The purpose of this paper is to describe the Enhanced PFAS Spatial Analysis study rationale, study design, and methods.
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spelling doaj-art-b8236a53832a49719b180c487d5c64c12025-01-26T12:38:11ZengBMCBMC Cancer1471-24072025-01-0125111110.1186/s12885-025-13508-2Enhanced spatial analysis assessing the association between PFAS-contaminated water and cancer incidence: rationale, study design, and methodsResa M. Jones0Erin R. Kulick1Ryan Snead2Robin Taylor Wilson3John Hughes4Ted Lillys5Department of Epidemiology and Biostatistics, College of Public Health, Temple UniversityDepartment of Epidemiology and Biostatistics, College of Public Health, Temple UniversityDepartment of Epidemiology and Biostatistics, College of Public Health, Temple UniversityDepartment of Epidemiology and Biostatistics, College of Public Health, Temple UniversityDepartment of Community and Population Health, College of Health, Lehigh UniversityResearch Triangle InstituteAbstract Background Cancer is a complex set of diseases, and many have decades-long lag times between possible exposure and diagnosis. Environmental exposures, such as per- and poly-fluoroalkyl substances (PFAS) and area-level risk factors (e.g., socioeconomic variables), vary for people over time and space. Evidence suggests PFAS exposure is associated with several cancers; however, studies to date have various limitations. Few studies have used rigorous spatiotemporal approaches, and, to our knowledge, none have assessed cumulative exposures given residential histories or incorporated chemical mixture modeling. Thus, spatiotemporal analysis using advanced statistical approaches, accounting for spatially structured and unstructured heterogeneity in risk, can be a highly informative strategy for addressing the potential health effects of PFAS exposure. Methods Using population-based incident cancer cases and cancer-free controls in a 12-county area of southeastern Pennsylvania, we will apply Bayesian spatiotemporal analysis methods using historically reconstructed PFAS-contaminated water exposure given residential histories, and other potential cancer determinants over time. Bayesian group index models enable assessment of various mixtures of highly correlated PFAS chemical exposures incorporating mobility/residential history, and contextual factors to determine the association of PFAS-related exposures and cancer incidence. Discussion The purpose of this paper is to describe the Enhanced PFAS Spatial Analysis study rationale, study design, and methods.https://doi.org/10.1186/s12885-025-13508-2BayesianCancer incidenceIndex modelPFASResidential historySpatiotemporal
spellingShingle Resa M. Jones
Erin R. Kulick
Ryan Snead
Robin Taylor Wilson
John Hughes
Ted Lillys
Enhanced spatial analysis assessing the association between PFAS-contaminated water and cancer incidence: rationale, study design, and methods
BMC Cancer
Bayesian
Cancer incidence
Index model
PFAS
Residential history
Spatiotemporal
title Enhanced spatial analysis assessing the association between PFAS-contaminated water and cancer incidence: rationale, study design, and methods
title_full Enhanced spatial analysis assessing the association between PFAS-contaminated water and cancer incidence: rationale, study design, and methods
title_fullStr Enhanced spatial analysis assessing the association between PFAS-contaminated water and cancer incidence: rationale, study design, and methods
title_full_unstemmed Enhanced spatial analysis assessing the association between PFAS-contaminated water and cancer incidence: rationale, study design, and methods
title_short Enhanced spatial analysis assessing the association between PFAS-contaminated water and cancer incidence: rationale, study design, and methods
title_sort enhanced spatial analysis assessing the association between pfas contaminated water and cancer incidence rationale study design and methods
topic Bayesian
Cancer incidence
Index model
PFAS
Residential history
Spatiotemporal
url https://doi.org/10.1186/s12885-025-13508-2
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